Understanding Danmaku's potential in online video learning

Yaxing Yao, Jennifer Bort, Yun Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Danmaku is a video comment feature which is used to overlay comments onto videos of many types and is gaining popularity in China. In this paper, we explore Danmaku's potential in online video learning. We present our survey results of 213 Chinese online users regarding their usage of danmaku. We also propose a new design in which danmaku is modified and leveraged to better facilitate user engagement and interaction in an online learning environment. Our results show that participants perceived both designs to have many benefits in terms of social presence and cognitive presence. Most of the participants post danmaku themselves instead of simply watching others' danmaku. In addition, about 40% of the participants who did not prefer the original design showed more positive feedback in the new design.

Original languageEnglish (US)
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages3034-3040
Number of pages7
VolumePart F127655
ISBN (Electronic)9781450346566
DOIs
StatePublished - May 6 2017
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
CountryUnited States
CityDenver
Period5/6/175/11/17

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Keywords

  • Community of inquiry
  • Danmaku
  • Interface design
  • Online video learning
  • Social presence
  • Video comments

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Yao, Y., Bort, J., & Huang, Y. (2017). Understanding Danmaku's potential in online video learning. In CHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire (Vol. Part F127655, pp. 3034-3040). Association for Computing Machinery. https://doi.org/10.1145/3027063.3053258